Measuring and Protecting User Privacy

Members and Collaborators

Overview

User privacy is exposed to many risks, from unintentional and unwanted data sharing to data collection without user consent. Our research seeks to measure privacy risks and prevent them by developing better user control over their data

Critter

Critter@home is a project to connect researchers to content-rich data from anonymous Internet end-users. Our goal is to facilitate the safe sharing of data and provide a platform for end-users to contribute data and be part of the research process.

Measuring Venmo Privacy Risks

Venmo online payment platform makes user data public by default. In this project we measured the risks this poses to users and how user behavior adapts to lower these risks.

Privacy-Safe Data Sharing

In this research we looked into privacy-safe data queries. Such queries are analyzed and data is aggregated to enforce strong k-anonymity.

Publications

I know what you did on Venmo: Discovering privacy leaks in mobile social payments, Rajat Tandon, Pithayuth Charnsethikul, Ishank Arora, Dhiraj Murthy and Jelena Mirkovic, In Proceedings of Privacy Enhancing Technologies Symposium (PETS), 2022PDF BIB
Samba: Identifying Inappropriate Videos for Young Children on YouTube, Le Binh, Rajat Tandon, Chingis Oinar, Jeffrey Liu, Uma Durairaj, Jiani Guo, Spencer Zahabizadeh, Sanjana Ilango, Jeremy Tang, Fred Morstatter, Simon Woo and Jelena Mirkovic, In Proceedings of 31st ACM International Conference on Information & Knowledge Management (CKIM), 2022PDF BIB
Commoner Privacy And A Study On Network Traces, Xiyue Deng and Jelena Mirkovic, In Proceedings of the Annual Computer Security Applications Conference (ACSAC), 2017PDF BIB
Critter: Content-Rich Traffic Trace Repository, V. Sharma, G. Bartlett and J. Mirkovic, In Proceedings of Workshop on Information Sharing and Collaborative Security (WISCS), 2014PDF BIB

This material is based upon work supported by the National Science Foundation under grant #1319215 and #1815495, and by the Science and Technology Directorate of the United States Department of Homeland Security under contract number D15PC00184. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the National Science Foundation nor the Department of Homeland Security.